Search Profiles

Search infrastructure is often treated as a separate concern from the data model. A search engineer writes index mappings in JSON. A data architect designs entity-relationship models. The two artefacts exist in different repositories with no formal connection. When the data model changes, the search index may or may not be updated. When a new field is added to the search index, it may or may not correspond to a real model property.

Search profiles bridge this gap by making search index configuration a first-class part of the model. Each model property can carry search-specific metadata (searchable, filterable, sortable, analyser, boost, vector dimensions), and each search profile defines how abstract types map to engine-specific field types. The result is search index configuration that is traceable back to the model and governed by the same lifecycle and validation rules.

Supported Search Engines

Profile Configuration

Each search profile contains engine-level settings that apply to all entities projected through it.

Operational Strategies

Search profiles go beyond schema configuration to include operational concerns that are critical for production search infrastructure.

Index Lifecycle Management

For time-series and high-volume indexes, search profiles support lifecycle policies that move data through temperature tiers.

Rollover Configuration

Rollover policies control when a new index is created to prevent any single index from growing too large.

Search Drift Detection

The Search Drift Detection service compares the design-time schema (model properties + search profile) against a deployed search index to identify discrepancies.